Boltzmann Distribution

The Boltzmann distribution describes the probability of a system being in a particular state at a given temperature, a fundamental concept in statistical mechanics with broad applications. Current research focuses on efficiently sampling from Boltzmann distributions, particularly for high-dimensional systems, using various generative models like normalizing flows, diffusion models, and energy-based models, often incorporating techniques like importance sampling and bootstrapping to improve accuracy and efficiency. These advancements are crucial for diverse fields, including molecular dynamics simulations, materials science, and machine learning, enabling more accurate modeling and prediction of complex systems.